International Business Machines Corporation

University of California

Icahn School of Medicine at Mount Sinai

Mount Sinai School of Medicine

Avi Ma'ayan

Gustavo Alejandro Stolovitzky

John Michael Wagner

Guillermo A Cecchi

Ravishankar Rao

Len A Pennacchio

Bruce D Gelb

Marco Tartaglia

Ravi Iyengar

Srinivas Ravi Viraraghava Iyengar

The present invention is directed to methods of diagnosing Noonan-like syndrome with loose anagen hair comprising detecting a mutation in SHOC2 gene. One specific diagnostic mutation disclosed is an A-to-G transition at position 4 resulting in a mutation at position 2 of SHOC2 amino acid sequence from serine to glycine. The invention also provides related sequences and kits.

SHOC2 mutations causing noonan-like syndrome with loose anagen hair

Methods, systems and apparatus for characterizing networks are presented. For example, a method of characterizing a network represented by a plurality of nodes and a plurality of edges is provided. The method may be implemented on a processor device and includes calculating, for example, by the processor device, a passthrough count of at least a portion of the network. The passthrough count includes a count of a number of passthroughs in the at least a portion of the network. A passthrough includes one of the plurality of nodes, a directed edge of the plurality of edges coupled to the one of the plurality of nodes, and another edge of the plurality of edges coupled to the one of the plurality of nodes. At most one of the directed edge and the other edge is directed towards the one of the plurality of nodes. At most one of the directed edge and the other edge is directed away from the one of the plurality of nodes.

Network characterization, feature extraction and application to classification

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Avi Ma'ayan